Data Scientist with Petroleum Engineering experience establishing Data Connection and Pipelines

Resume Information


Data Scientist with 2 years' experience interpreting oil & gas economic data, data-wrangling, and calculating predictions to support intelligent business decisions using Big Data platforms. Proven results in project management, machine learning, computation skills, pattern recognition, ETL and data pipelines.

Houston, Tx
DATA SCIENCE DEVELOPMENTS • Oil & Gas Well Initial Production Prediction (Current): Predict well’s first month oil & gas initial production (IP) using big data. Characteristics such as proppant, lateral length, frac fluid volume, etc. combined from 3 SQL databases then GBM, Random Forest, K-Means, SVM, and Naïve Bayes algorithms in R predict IP with nearly 40% accuracy • Correlative & Predictive US Health Statistics (September 2019): Utilized U.S. public health dataset to correlate and predict high-risk health behaviors leading to premature death • Call Log Database (June 2019): Developed Azure SQL Database for analysis and management of company relations via Azure Cloud. Sequences bid negotiations for land acquisitions team and monitors conversation progress • Oil and Gas Well Ownership App (May 2019): Led team-based project to normalize index data from Azure SQL and Access databases that were previously siloed allowing for accessibility via Power Bi, Azure Cloud services; promoted transparency of hydrocarbon-bearing land acquisitions PROFESSIONAL EXPERIENCE Data Scientist│Petroleum Engineer, Cosmo Energy LLC, Oklahoma City, OK Sept 2017-Nov 2019 • Designed and implemented Revenue and JIB Data Pipeline and Processing project for 900 wells, 4100 net mineral acres using web scraping software, Optical Character Recognition (OCR), Python HTML parsing, and SQL • Forecasted revenue from hydrocarbon production on $4 million acquisition package using Aries and in-house models. Prepared executive summary highlighting key values and rate of return timeline • Eliminated $7,200 in annual costs by implementing Agile process improvements for an interdisciplinary team • Developed and analyzed Joint Interest Billings (JIB) database for 800 + records, providing clear expectation of expenses associated with lease ownerships; developed more accurate net revenue predictions for acquisitions • Constructed live GIS map for oil & gas activity surrounding company ownerships. Python script extracted data from public sources, filtered based on release date and category, then mapped information based on spatial relevance Engineering Intern, National Oilwell Varco, Tulsa, OK May 2017-Jan 2018 • Coordinated a team to redesign inventory layout and scheduling to optimize the manufacturing process; which increased production by 12% and $2000 in monthly savings, ultimately ensure timely and complete customer delivery • Synthesized database corporation-wide, eliminating duplicate and mislabeled products. Resulting database clarified production orders and inventory confusion. Construction Intern, Chicago Bridge and Iron (CB&I), Ingleside, TX Jan-Aug 2015 • Conducted inspections, inventory, structural readings & installments on pipe racks, cooling towers and ethylene cracker Office Administrator, Allcare Products, Houston, TX June-Dec 2014 • Managed company payroll, accounts payables & receivables in addition to banking relations
TECHNICAL SKILLS Data Science Tools: R, Python, Power BI , Tableau, Google Analytics Data Engineering Tools: SQL, Hadoop, Pandas, MongoDB, Azure 3rd Party API: Oseberg, DrillingInfo, IHS Markit
M.S. in Applied Data Science, Syracuse University, Syracuse, NY, September 2020 GPA:3.95/4.00 B.S. in Petroleum Engineering, University of Oklahoma, Norman, OK, December 2018 • Minor: Geographic Information Systems